E. coli death phase population consists of live cells that are metabolically inactive.
In a batch culture, a typical bacterial growth curve consists of 5 distinct phases, i.e., lag phase, exponential phase, stationary phase, death phase and finally followed by a long-term stationary phase that is maintained for years (13). The death phase in the growth curve has been considered for a long time as a stochastic event. When the cultural environment can no longer support the growth due to its limited resources in terms of nutrition, space and steady build-up of toxic metabolites, it causes cell death. When we examined cells from different stages of the growth curve, we observed a sharp decrease in the ability of E.coli to form colonies by 72 hours (Fig. 1A). However, we did not notice any substantial increase in the dead cell population (Fig. 2A). We observed that by 72 hours there was an approximate 95% drop in the ability of E. coli to grow in a LB agar plate (Fig. 1A). Whereas, when the same population was observed under microscope after staining with a live-dead stain, almost all the cells stained green, showing live cells (Fig. 2A). To further negate that the decrease in the colony forming units (cfu) was not due to the decrease in the actual cell numbers, we calculated the total number of cells by measuring the scattering at 600 nm (OD600) and counting the number of cells using a flow cytometer. The results showed an initial increase in the total relative cell counts till 40 hrs which remained unchanged until 96 hrs (Fig. 1C & D). We also found that the steady state E. coli was not affected by ampicillin, whereas, can be inhibited by rifampicin (Fig. S1). We determined the metabolic activity of the bacterial cells at various time points (Fig. 1B). The result showed an increase in the metabolically active cells until 40 hrs, which then decreased to near zero by 72 hrs. This data correlated with the cfu count data. Hence, we conclude that the death phase population of the E.coli growing in a batch culture mainly consisted of live cells with reduced metabolic activity, and have lost their ability to grow on solid LB agar plates.
E. coli death phase population does not show hallmarks of apoptosis.
Historically the death phase in a batch culture has been considered to be mainly comprised of dead or dying cells. Due to nutrient and space limitations the cells can no longer grow and eventually stochastically die (14). However, recent evidences suggest that programmed cell death may be a viable strategy in prokaryotes (15–17). So, with this initial assumption we wanted to shed light on the mode of death during bacterial death phase. To prove this, we checked for the presence of two well characterized apoptotic markers i.e. Phosphatidylserine (PS) exposure and DNA fragmentation, in various stages of growth in a batch culture. It has been shown earlier that bacteria when exposed to antibiotics test positive for these markers showing apoptotic like death (18). However, the late stationary phase cells and the death phase cells did not show any increase in either PS exposure or DNA fragmentation (Fig. 3A &B). Interestingly, we also did not see an increase in cells stained with propidium iodide which indicates the lack of dead cells in the bacterial death phase. These results corroborate our initial finding that the death phase population mainly comprise of live cells which have lost their ability to grow on LB agar plates. As a positive control we used kanamycin treated cells and they showed an increase in the propidium iodide and PS exposure (Fig. 3A)
Loss in membrane polarity in the later stages of a batch culture indicates increase in persistent phenotype.
The cell membrane in bacteria is a semipermeable membrane that protects the cell from many outer stresses including antibiotics. All living cells inherently and actively maintain a potential difference across its membrane thereby generating a membrane potential (19). It is now known that the membrane potential is responsible for a wide range of signalling and processing. From pH homeostasis to cell division and even environmental sensing the bacterial membrane potential is dynamic tool (20). Many antibacterial compounds achieve their goal by altering the membrane potential of the cell. Recent reports showed that some antibiotics can induce membrane depolarization and kill bacteria (21–23). Alternatively, it is also shown that mild increases in membrane depolarization achieved by the cell itself in response to stresses can promote persister formation (24, 25). We observed that E.coli grown in a batch culture tend to mildly increase its membrane potential in the whole population at different time points (6 hrs – 72 hrs) (Fig. 3C).This supported the idea that the persister formation in steady state of the growth phase might have increased due to change in membrane potential.
Expression of the MazEF-TA modules increases overtime in a batch culture of the E. coli.
The role of the TA modules in the bacteria is highly debatable. There are reports that suggest TA modules play an important role during bacterial programmed cell death, whereas, others advocate their roles during persister formation. Several type II TA modules are known to induce the persister formation in various bacteria. For example, overexpression of several toxins (i.e., TisB, HokB, etc.) reportedly increases the number of persister formation, whereas, deletion of the toxins decrease the number of persistent cells (26–28). MazEF is one of the TA module that has been extensively studied and several reports support their role in the persister formation in different bacteria (9, 29, 30). In E. coli, the MazF expression leads to growth arrest and enhance its survivability against various stresses (9, 31). To understand the role of different TA modules during the death phase of the E. coli, we quantified the expression of MazEF along with five other Type-II TA modules (ChpBK/S, HicAB, MsqRA, RelEB, YoeB/YefM) using qRT-PCR. Our result showed that the expression of all the tested TA modules increased with increasing time (Fig. 2B & Fig. S2). Compared to the log phase (6 hrs) bacteria, the amount of MazEF increased nearly 2 folds in the steady state (48 hrs) and the death phase (72 hrs). Compared to the log phase, the number of persisters are reported to be higher during the steady state and the death phase of bacteria. Thus, our finding suggests that the higher MazEF expression may be related to higher persister formation in E. coli. As the MazEF TA system is well regarded as one of the factors responsible for the persister formation, we further focused our study to understand its interaction with rifampicin, a persister modulator.
Rifampicin directly interacts with the MazEF complex.
Persisters can tolerate antibiotics not by acquiring any resistance, but through slowing down their metabolism. The activation of MazEF-TA module increases the number of persisters, whereas, bacteria lacking MazF becomes more susceptible to antibiotics (27, 30). These observations suggested that targeting MazEF may provide a clue to target the persisters. To identify the molecules that can interact with the MazEF complex and inhibit bacterial growth, we performed molecular docking of MazEF complex, MazE or MazF with molecules from an FDA approved drug library containing 800 drug molecules. The 10 best ranked drugs against MazE, and MazF are shown in (Supplementary Table 1). Further analysis of the molecular docking data revealed that rifampicin has higher affinity (-8.3 Kcal/mol) for MazE structure than MazF (-6.2 Kcal/mol). In agreement with this data, rifampicin was found to bind in the deep pocket of MazE (Fig. 4A), whereas, for MazF it shows interaction on the surface (Fig. 4B). The molecular docking of rifampicin was carried out against the MazEF complex (PDB ID: 1UB4, chain A and C). As shown in the figure, rifampicin is predicted to preferentially interact in the same cavity of MazE (Fig. 4C). The in silico data suggested that among the screened molecules rifampicin has a strong affinity against MazEF complex. Rifampicin is an antibiotic used for treatment of tuberculosis where persistence is a major problem. It is known to induce antibiotic tolerance in mycobacteria and higher dose can kill the persisters and reduce the duration of the treatment (11, 32).
To confirm the direct interaction of MazEF with rifampicin, we purified the MazEF complex (Fig. S3) and performed the interaction studies with rifampicin using fluorescence binding assay. Our biochemical data shows that rifampicin interacts moderately with MazEF complex with a dissociation constant of 42 ± 8 µM (Fig. 4D). To verify that the interaction of rifampicin with MazEF complex is a specific one, we determined the interaction of ampicillin with MazEF complex. Ampicillin did not affect the persister formation and was previously used by several researchers to kill the normal bacteria and enrich the persisters. Interestingly, our in-silico data showed that ampicillin does not interact with the MazE. The affinity of ampicillin with MazE was calculated to be -6.4 Kcal/mol which is much lower as compared to the interaction between rifampicin-MazEF complex (-8.3 Kcal/mol). Similarly, fluorescence binding assay did not show any significant change in the fluorescence of MazEF complex when titrated against ampicillin, suggesting that ampicillin does not interact with MazEF complex (data not shown).